Cross-border travel in Europe is freer than almost anywhere else in the world. It might therefore seem that the borders between European countries are becoming less important and that passengers do not even think about them when choosing their travel destination. However, even in a highly integrated and liberalised region such as Europe, the border still appears as a negative factor when looking at transport supply and demand figures. Borders continue to act as barriers to some extent.

The aim of this paper is to provide reliable estimates of these negative border effects and to analyse possible determinants of such negative effects. This topic is often studied with a focus on trade, but there are only a few studies dealing with border effects in the field of long-distance passenger transport, especially in Europe. As these studies do not cover the whole of Europe or do not go into depth, there is a gap that needs to be filled. Knowing the magnitude of negative border effects is crucial and valuable for various actors, such as transport policymakers, airport operators or air service providers.

The magnitudes of border effects will be obtained using different specifications of gravity models based on origin-destination data. In addition, various factors that could influence these values will be examined. The primary estimation is based on OAG supply data using OECD/Eurostat functional urban areas (FUAs) as spatial units. Estimates from supply models will be compared with those from demand models using Eurostat data. The novelty of this paper also lies in the consideration of multiple spatial units, when the results obtained using FUAs are compared with those obtained using NUTS 3 or metropolitan regions from Eurostat. To understand how the values of border effects evolve over time, part of the analysis is carried out on panel data. In addition, the geographical distribution of border effects will be examined in order to identify spatial differences in the integration process. Further spatial differences will also be identified by mapping residuals, which should help to think beyond the models.

Railways are essential for landlocked states to secure cost-effective access to major export and import markets, which is critical for overcoming trade bottlenecks imposed by geography. However, Central Asia, a landlocked region, has historically faced significant limitations due to its underdeveloped railway infrastructure. Unlike the advanced rail networks at the eastern and western ends of Eurasia, Central Asia’s railway system lags behind, hindering regional connectivity. The improvement of railway links in this region is not only vital for Central Asia’s economic growth but also for enhancing the overall accessibility of the Eurasian continent. This paper examines how the completion of planned cross-border railway projects will transform Central Asia's connectivity with other Eurasian regions. Utilizing existing cross-border railway planning documents, the study simulates changes in accessibility resulting from the development of major trans-Eurasian rail corridors. It assesses the potential impact on travel times, logistics efficiency, and connectivity between key Eurasian regions, particularly Central Asia, China, Russia, and Europe. By comparing current and projected transport scenarios, the paper provides insights into how the expanded rail network will improve cross-continental movement, foster greater integration, and bridge gaps between less-connected regions. The study underscores the importance of railway infrastructure in improving geographic accessibility and enhancing the overall transport connectivity of Eurasia.

Border effects in global port shipping are reflected in the competitiveness of cross-border ports and the complementarity of domestic ports. For both export and import ports: the market diversification strategy determines the competitive relationships among cross-border ports; the shared hinterland and the redundant routes coping with risks determine the complementary relationships among domestic ports. Thus, based on the dimensions of “Port of Loading (POL) – Port of Discharge(POD)” and “Competitiveness – Complementarity”, four types of shipping networks that reflect border effects exist. Previous studies only investigated the competitiveness of import countries, resulting in the masking of the ports' role and the complementary relationship. Exporters have also not been considered.

To fill these gaps, this paper constructed the “POL-POD-Competitiveness-Complementarity (PPCC)” theoretical framework, and used the Export Similarity Index to construct the PPCC Intensity Model. The global iron ore trade flow, which hold significant importance for national economy and strategic security, was selected as the research object. The research data came from Automatic Identification System (AIS) and GoGo-TRADE Vessel Report System. Complex Network Methods were applied to construct the global iron ore trade flow PPCC network and measure the multiple border effects.

The results are as follows: (1) 90% of cross-border ports competitiveness intensity and 50% of domestic ports complementarity intensity are very small, indicating that the border effects of port shipping are mainly reflected among a few core ports. From the extreme values of competitiveness intensity of POL and POD, the former is 4 times higher than the latter, proving that the competitiveness of exporters is more imbalanced and cannot be ignored anymore. (2) In the competitiveness network of 109 POLs, ports in Australia, Brazil, and India are the core, while ports in East Asia are the core in the competitiveness network of 271 PODs. From the complementarity networks of various countries, it can be found that the domestic ports with long-distance and high-complementarity intensity are the most noteworthy, which could significantly enhance the resilience of the country in the shipping supply chain. (3) Competitiveness and complementarity in cross-border shipping were aggregated at the national level, and four types of countries were identified. The results revealed that China as an exporter and South Korea as an importer do not match in terms of their trade volume and cross-border transportation advantages.

As one of the most important cross-border railway networks in the world, the Trans-European Transport Network (TEN-T) provides opportunities to enhance social and economic integration among countries it connects. Although there is extensive research on how railways transform inter-city connections and facilitate passengers and freight flows within a single-country, studies on cross-border railways remain notably scarce. Unlike railway studies focused on a single country, analysing borders — one of the most significant factors in cross-border networks — requires nuanced approaches and methods. In this study, we propose a simple but generic method to explore the extent to which borders, such as those caused by differences in railway gauge, affect the centrality and efficiency of nodes (cities) and corridors at a network scale. This approach has been applied to the TEN-T using multiple simulation scenarios. Our findings confirm that, according to the topologic structure of TEN-T, countries situated near the geometric center of the network exhibit strong connectivity. Within the TEN-T, Paris and Berlin emerge as well-connected hubs. Regarding transport corridors, the Rhine - Alpine corridor and the North Sea - Mediterranean corridor demonstrate robust connectivity. Using simulation, we further show that when gauge-related border delays are introduced in peripherical areas, such as between France and Spain or Poland and Lithuania, a 5-hour delay at these borders results in measurable effects on betweenness centrality. Specially, the centrality of Spain and Lithuania decreases by 0.57% and 0.37%, respectively, while the centrality of France and Poland increases by 2.12% and 5.13%. Additionally, these border effects significantly diminish the geographic advantage of Berlin. This study highlights that border effects influence not only the regions near borders but also those with geometric centrality. These findings suggest a need to re-evaluate the geographical decay of border effects in cross-border railway networks.